The Algorithm of Neural Networks on the Initial Value Problems in Ordinary Differential Equations

摘要：

A new method for solving Initial Value problems in Ordinary Differential Equations (ODEs) is proposed in this paper. The algorithm of neural networks based on the cosine basis functions is studied in detail. The convergence theorem of neural networks algorithm is given and proved. The algorithm is validated by the simulation examples of ODEs. The results show the proposed approach is more precise than modified Euler Method and Heuns Method.

关键词： Neural Network Cosine Basis Functions Ordinary Differential Equations convergence theorem

作者: Liying XU Hui WEN Zhe-zhao ZENG

作者单位: Changsha University of Science and Technology, China

会议类型: 国际会议

会议名称: 2nd IEEE Conference on Industrial Electronics and Applications(ICIEA 2007)(第二届IEEE工业电子与应用国际会议)

会议地点: 哈尔滨

会议语种:英文

在线出版日期: 2007-05-23（万方平台首次上网日期，不代表论文的发表时间）